This book describes a set of methods for finding more-for-less solutions of various kind of fuzzy transportation problems. Inspired by more-for-less approaches to the basic transportation problem initiated by Abraham Charnes and his collaborators during 1960s and 1970s, this book describes new methods developed by the authors to solve different types of problems, including symmetric balanced fuzzy transportation problems, symmetric intuitionistic fuzzy transportation problems with mixed constraints, and symmetric intuitionistic fuzzy linear fractional transportation problems with mixed constraints. It offers extensive details on their applications to some representative problems, and discusses some future research directions

This book presents a novel approach to the formulation and solution of three classes of problems: the fully fuzzy transportation problem, the fully fuzzy transshipment problem, and fully fuzzy solid transportation problem. It points out some limitations of the existing formulations and approaches, indicating some possible, conceptually and algorithmically attractive solutions to alleviate them. In particular, the book describes new conceptual and algorithmic solutions for finding the fuzzy optimal solutions of the single-objective fully fuzzy transportation problems, the fully fuzzy transshipment problems and the fully fuzzy solid transportation problems. Moreover, based on the novel concepts and solutions proposed by combining the concept of a fully fuzzy solid transportation problem and a fully fuzzy transshipment problem, it describes a new class of problems, i.e. the fully fuzzy solid trans-shipment problem, together with its fuzzy linear programming formulation and some methods to find its fuzzy optimal solution. The book offers the readers a timely piece of literature in the field of fuzzy linear programming, and is expected to act as a source of inspiration for future research and applications.

George Dantzig is widely regarded as the founder of this subject with his invention of the simplex algorithm in the 1940's. In this second volume, the theory of the items discussed in the first volume is expanded to include such additional advanced topics as variants of the simplex method; interior point methods, GUB, decomposition, integer programming, and game theory. Graduate students in the fields of operations research, industrial engineering and applied mathematics will thus find this volume of particular interest.

This book presents a novel approach to the formulation and solution of three classes of problems: the fully fuzzy transportation problem, the fully fuzzy transshipment problem, and fully fuzzy solid transportation problem. It points out some limitations of the existing formulations and approaches, indicating some possible, conceptually and algorithmically attractive solutions to alleviate them. In particular, the book describes new conceptual and algorithmic solutions for finding the fuzzy optimal solutions of the single-objective fully fuzzy transportation problems, the fully fuzzy transshipment problems and the fully fuzzy solid transportation problems. Moreover, based on the novel concepts and solutions proposed by combining the concept of a fully fuzzy solid transportation problem and a fully fuzzy transshipment problem, it describes a new class of problems, i.e. the fully fuzzy solid trans-shipment problem, together with its fuzzy linear programming formulation and some methods to find its fuzzy optimal solution. The book offers the readers a timely piece of literature in the field of fuzzy linear programming, and is expected to act as a source of inspiration for future research and applications.

"Optimizing Multi-Objective and Fuzzy Transportation" explores cutting-edge approaches to address complex transportation problems that involve multiple conflicting objectives and uncertainties represented using fuzzy logic. This multidisciplinary field combines elements of operations research, optimization, and fuzzy set theory to provide practical solutions for real-world transportation challenges. In today's dynamic and interconnected world, transportation networks are becoming increasingly complex, necessitating innovative optimization techniques. This book delves into the intricacies of multi-objective optimization, where decision-makers must balance conflicting objectives such as cost minimization, time efficiency, and environmental sustainability. Moreover, it addresses the inherent uncertainties in transportation systems by employing fuzzy logic to model and analyze imprecise information. Readers will gain insights into state-of-the-art methodologies, algorithms, and case studies, showcasing how these tools can be applied to diverse transportation scenarios. From supply chain management and urban transportation planning to logistics and distribution, this book offers valuable guidance for practitioners, researchers, and students seeking to optimize transportation systems under multiple objectives and fuzzy conditions. "Optimizing Multi-Objective and Fuzzy Transportation" is a comprehensive resource that bridges the gap between theory and practice, fostering innovative solutions for the ever-evolving challenges in transportation optimization.

In this contribution, for the first time, an effcient model of multi-objective product blending fixed-charge transportation problem with truck load constraints through transfer station is formulated.

This book presents the very concept of an index matrix and its related augmented matrix calculus in a comprehensive form. It mostly illustrates the exposition with examples related to the generalized nets and intuitionistic fuzzy sets which are examples of an extremely wide array of possible application areas. The present book contains the basic results of the author over index matrices and some of its open problems with the aim to stimulating more researchers to start working in this area.